• Current Optics and Photonics
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• v.4 no.4
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• pp.286-292
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• 2020

Imaging through multicore fiber (MCF) is of great significance in the biomedical domain. Although several techniques have been developed to image an object from a signal passing through MCF, these methods are strongly dependent on the surroundings, such as vibration and the temperature fluctuation of the fiber's environment. In this paper, we apply a new, strong technique called deep learning to reconstruct the phase image through a MCF in which each core is multimode. To evaluate the network, we employ the binary cross-entropy as the loss function of a convolutional neural network (CNN) with improved U-net structure. The high-quality reconstruction of input objects upon spatial light modulation (SLM) can be realized from the speckle patterns of intensity that contain the information about the objects. Moreover, we study the effect of MCF length on image recovery. It is shown that the shorter the fiber, the better the imaging quality. Based on our findings, MCF may have applications in fields such as endoscopic imaging and optical communication.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.60-69
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• 2019

In this paper, we deal with forward-looking imaging, and focus on forward-looking synthetic inverse scattering imaging for a vehicle with curved motion. For image formation, time domain correlation(TDC) is used and a 2D image of the ground in front of the vehicle is generated. Because TDC is a technique that implements matched filtering for a space-variant system, it is robust to Gaussian additive noise of measurements. Furthermore, comparison and analysis between images from linear motion and curved motion show that the resolution of the image is improved; however, the entropy of the image is increased owing to curved motion.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.167-175
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• 2021

Semi-supervised learning uses both labeled data and unlabeled data. Recently consistency regularization is very popular in semi-supervised learning. Unsupervised data augmentation (UDA) that uses unlabeled data augmentation is also based on the consistency regularization. The Kullback-Leibler divergence is used for the loss of unlabeled data and cross-entropy for the loss of labeled data through UDA learning. UDA uses techniques such as training signal annealing (TSA) and confidence-based masking to promote performance. In this study, we propose to use Jensen-Shannon divergence instead of Kullback-Leibler divergence, reverse-TSA and not to use confidence-based masking for performance improvement. Through experiment, we show that the proposed technique yields better performance than those of UDA.

• Smart Media Journal
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• v.10 no.4
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• pp.45-54
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• 2021

The skin is the body's first line of defense against external infection. When a skin disease strikes, the skin's protective role is compromised, necessitating quick diagnosis and treatment. Recently, as artificial intelligence has advanced, research for technical applications has been done in a variety of sectors, including dermatology, to reduce the rate of misdiagnosis and obtain quick treatment using artificial intelligence. Although previous studies have diagnosed skin diseases with low incidence, this paper proposes a method to classify common illnesses such as warts and corns using a convolutional neural network. The data set used consists of 3 classes and 2,515 images, but there is a problem of lack of training data and class imbalance. We analyzed the performance using a deep metric loss function and a cross-entropy loss function to train the model. When comparing that in terms of accuracy, recall, F1 score, and accuracy, the former performed better.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.279-284
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• 2023

Isothermal titration calorimetry (ITC) is a useful technique to obtain thermodynamic binding properties such as enthalpy, Gibbs free energy, entropy, and stoichiometry of the chelation reaction. A single independent binding site model was used to evaluate the thermodynamic binding properties in BaCl₂ and ethylenediaminetetraacetic acid (EDTA) in Trince and HEPES buffers. ITC enables us to elucidate the binding mechanism and find an optimal chelation condition for BaCl₂ and EDTA in the pH range of 7~11. Chelation of BaCl₂ and EDTA is a spontaneous endothermic reaction. As pH increased, entropic contributions dominated. The optimal pH range is narrow around pH 9.0, where 1:1 binding between BaCl₂ and EDTA occurs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.9-21
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• 2004

In this paper, we proposed the image hiding method which decreases calculation amount by encrypt partial data using discrete wavelet transform and linear scale quantization which were adopted as the main technique for frequency transform in JPEG2000 standard. Also we used the chaotic system which has smaller calculation amount than other encryption algorithms and then dramatically decreased calculation amount. This method operates encryption process between quantization and entropy coding for preserving compression ratio of images and uses the subband selection method and the random changing method using the chaotic system. For ciphering the quantization index we use a novel image encryption algerian of cyclically shifted in the right or left direction and encrypts two quantization assignment method (Top-down/Reflection code), made change of data less. Also, suggested encryption method to JPEG2000 progressive transmission. The experiments have been performed with the proposed methods implemented in software for about 500 images. consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. It has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.173-180
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• 2005

In this paper, we proposed the image hiding method which decreases calculation amount by encrypt partial data using discrete wavelet transform(DWT) and linear scale quantization which were adopted as the main technique for frequency transform in JPEG2000 standard. Also we used the chaotic system and cat map which has smaller calculation amount than other encryption algorithms and then dramatically decreased calculation amount. This method operates encryption process between quantization and entropy coding for preserving compression ratio of images and uses the subband selection method. Also, suggested encryption method to JPEG2000 progressive transmission. The experiments have been performed with the Proposed methods implemented in software for about 500 images. Consequently, we are sure that the proposed is efficient image encryption methods to acquire the high encryption effect with small amount of encryption. It has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas.

• Membrane and Water Treatment
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• v.14 no.2
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.50-59
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• 2006

The new communication paradigm is rapidly shifted from wireless mobile networks to an All-IP(Internet Protocol) network, led by service industry leaders and communication manufacturers. In this paradigm, providing authentication and session keys of a subscriber becomes one of the critical tasks because of IP open accessibility among heterogeneous networks. In this paper, we introduce authentication process procedure of heterogeneous wireless mobile networks and develop so-called IMAS(Integrated Mobile Authentication Server) which can securely inter-work among all mobile networks and support the legacy networks with backward compatibility. Especially, in designing IMAS, mobile authentication inter-working mechanism, key management technique, and other issues to be overcome are presented. We analyze and evaluate the performance of authentication algorithm which creates session key. A simulation environment of IMAS is established, and a performance(TPS; Transaction Per Second) result is analyzed and evaluated. It turned out that IMAS works among heterogeneous wireless mobile networks without compensating efficiency and functionalities of the legacy networks and decrease the entropy of data redundancy and data inconsistency among networks because of the integrity of the distributed Data Base(DB).